This invention relates to the analysis and visualization of data features in a dataset. More specifically, visual features are detected among the dataset in a view-space, semantics of the visual features are described and identified, and interaction with the described visual features is supported to guide development and understanding of the dataset.
Information visualization is an increasingly vital tool at the disposal of decision makers to make data consumable. A good visualization reveals structure and patterns in data, and facilitates exploration of relationships. The challenge in exploratory visualization is to represent, and interact with complicated datasets, e.g. datasets having multiple dimensions. For example, for high dimensional data, visual representation may appear cluttered, resulting in challenges for interactive exploration. Accordingly, as the complexity and variety of data increase, so do the challenges for visualization and exploration of such data.
Advances in science, government, and business depends on the ability to analyze and comprehend data and to make decisions based on insight gained from such analysis. There is a need to improve the consumability of data for everyone involved in any kind of decision making throughput in an enterprise. Such a solution should enable a broad base of users, experts, and non-experts alike to deal with and develop an understanding of complex datasets.